We can use the function get_map() to pull a background map from google, OpenStreetMap (OSM) or Stamen.

    background <- get_map(location=c(lon = mean(berkeleyCrime$long),
                                     lat = mean(berkeleyCrime$lat)),
                          zoom=14,
                          maptype = "terrain",
                          source="google",
                          color="bw")
    
    map <- ggmap(background) + coord_equal() + 
      geom_point(data=berkeleyCrime, aes(x=long, y=lat, alpha=0.3, size=7, color=CVLEGEND)) +
      scale_size_continuous(range = c(3), guide=FALSE) +
      scale_alpha_continuous(range = c(.3), guide=FALSE)
    
    map

Leaflet is one of the most popular open-source JavaScript libraries for interactive maps. We can easily enable Leaflet and pull up the standard OpenStreetMap (OSM) baselayer using the following command:

leaflet() %>% addTiles() %>% addMarkers(lng = -122.258, lat = 37.870)

Try panning around and zooming in on this map, and notice how more and more data is loaded.

So what's with the %>% used in the previous example??

Throughout this presentation, I'll use something called a pipe which looks like this: %>% Pipes are a way of passing the result of one function into the next function. For example, the traditional way of pulling up a map with leaflet, adding tiles and then setting the view would be as follows:

addMarkers(addTiles(leaflet()), lng = -122.258, lat = 37.870).

Piping lets us flip the notation inside out, so it reads more naturally:

leaflet() %>% addTiles() %>% addMarkers(lng = -122.258, lat = 37.870).

See how the code in this second example reads like a recipe of what we want to do:

1. enable leaflet: leaflet() %>%
2. add background tiles: addTiles() %>%
3. set the view of the map: addMarkers(lng = -122.258, lat = 37.870)

You can read more about using pipes here and here.

Lets use out new knowledge of Leaflet to map the first 100 crimes in our berkeleyCrime dataset:

leaflet() %>% addTiles() %>% addMarkers(data=berkeleyCrime[1:100,])

For more information, pull up the help on any of the add functions in leaflet (e.g. ?addMarkers):

addMarkers(map, lng = NULL, lat = NULL, layerId = NULL, group = NULL, icon = NULL,
           popup = NULL, options = markerOptions(), clusterOptions = NULL,
           clusterId = NULL, data = getMapData(map))

addCircleMarkers(map, lng = NULL, lat = NULL, radius = 10, layerId = NULL, 
    group = NULL, stroke = TRUE, color = "#03F", weight = 5, opacity = 0.5, 
    fill = TRUE, fillColor = color, ....)

addTiles(map, urlTemplate = "http://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
         attribution = NULL, layerId = NULL, group = NULL, options = tileOptions())

addCircles(...)
addPolylines(...)
addRectangles(...)
addPolygons(...)
addPopups()
...

In this example, we change our markers to circleMarkers so we can adjust the color (and radius if we wish) and also add a popup that displays information when we click on the circle:

leaflet() %>% addTiles() %>%
      addCircleMarkers(data=berkeleyCrime[1:100,],
                       stroke = FALSE, fillOpacity = 0.5, radius=8,
                       popup=~paste("<strong>Offense:</strong>",CVLEGEND,
                       "<br>",
                       "<strong>Date:</strong>",EVENTDT,
                       "<br>",
                       "<strong>Time:</strong>",EVENTTM)
                       )

    #Create color palette
    offenseColor <- colorFactor(rainbow(25), berkeleyCrime$CVLEGEND)
    
    leaflet(berkeleyCrime[1:100,]) %>%
      addProviderTiles("CartoDB.Positron") %>%
      addCircleMarkers(
        stroke = FALSE, fillOpacity = 0.5, radius=6,
        color = ~offenseColor(CVLEGEND),
        popup = ~paste("<strong>Offense:</strong>",CVLEGEND,
                       "<br>",
                       "<strong>Date:</strong>",EVENTDT,
                       "<br>",
                       "<strong>Time:</strong>",EVENTTM)
      ) %>%
      addLegend(title = "Type of Offense", pal = offenseColor,
                values = ~CVLEGEND, opacity = 1, position="bottomleft")

• Adding color coding by crime type
• Adding legend

If we want to view many crimes, say all 4,598 crimes in this dataset, we may want to cluster our results. Displaying that many points at once will slow down our computer, and it just hard to visually process. Do cluster results in leaflet, we use the clusterOptions variable with markers or circleMarkers.

leaflet(berkeleyCrime) %>%
      addProviderTiles("CartoDB.Positron") %>%
      addCircleMarkers(
        stroke = FALSE, fillOpacity = 0.5, radius=6, color = ~offenseColor(CVLEGEND),
        clusterOptions = markerClusterOptions(spiderfyDistanceMultiplier=2, maxClusterRadius=60),
        popup = ~paste("<strong>Offense:</strong>",CVLEGEND,
                       "<br>",
                       "<strong>Date:</strong>",EVENTDT,
                       "<br>",
                       "<strong>Time:</strong>",EVENTTM)
      ) %>%
      addLegend(title = "Type of Offense", pal = offenseColor,
                values = ~CVLEGEND, opacity = 1, position="bottomleft")

Loading a shapefile of Yosemite National Park and a section of the PCT.

#load data
yosemite <- readOGR("./data/yosemite", "yosemite", verbose = FALSE) #yosemite boundary shapefile
PCT <- readOGR("./data/PCT.geojson", "OGRGeoJSON", verbose=FALSE)

#make map
leaflet() %>% addTiles() %>% addPolylines(data = yosemite) %>% addPolylines(data = PCT, color="red")

#load peaks points
peaks <- readOGR("./data/peaks.geojson", "OGRGeoJSON", verbose=FALSE)

#convert peak values to numeric
peaks <- subset(peaks, peaks@data$ele!="0")
peaks@data$ele <- round(as.numeric(levels(peaks@data$ele))[peaks@data$ele] * 3.28084)

#make map of peaks
leaflet() %>%
  addTiles() %>%
  addCircleMarkers(data=peaks, weight=0, radius=8, fillOpacity=0.6,
                   popup=~paste("Name: ",name,"<br>Elevation: ",ele,"feet")) %>%
  addPolylines(data=yosemite, fillOpacity = 0, dashArray=c(10,10), fill=FALSE, color="red")

Similarly to how we colored crimes by type of crime, we can size these circles based on their elevation using the code: radius=~ele/1000.

I've also added a marker using an icon to the subset of all peaks that are over 10,000 feet. To do this, we first set the icon setting using the function icons() and then usingaddMarkers with the subset of peaks data=subset(peaks, peaks@data$ele>10000)

#mountain icon settings
peakIcons <- icons(
  iconUrl = "./data/Mountain-512.png",
  iconWidth = 15, iconHeight = 15,
  iconAnchorX = 7.5, iconAnchorY = 8.5
  )

leaflet() %>%
  addTiles() %>%
  addCircleMarkers(data=peaks, weight=0, radius=~ele/1000, fillOpacity=0.7, 
                   popup=~paste("Name: ",name,"<br>Elevation: ",ele)) %>%
  addMarkers(data=subset(peaks, peaks@data$ele>10000),
             icon = peakIcons,
             popup=~paste("Name: ",name,"<br>Elevation: ",ele)) %>%
  addPolylines(data=yosemite, fillOpacity = 0, dashArray=c(10,10), fill=FALSE, color="red")

Lets add some color to our circles. Do do this, we create a palette, just like we did for Berkeley crimes. In this example, there is an extra line where I first define the palette spectral so I can flip the color scheme. Then we map elevations to the palette in the line that begins eleColor.

To add a legend to the map, we use the function addLegend() and assign the pal to the mapped palette eleColor.

#create color scale from elevation
spectral <- brewer.pal(11, "Spectral")  %>% rev()
eleColor <- colorBin(spectral, peaks@data$ele)

leaflet(peaks) %>%
  addTiles() %>%
  addCircleMarkers(weight=0, radius=~ele/1000, fillOpacity=0.7, color = ~eleColor(ele),
                   popup=~paste("Name: ",name,"<br>Elevation: ",ele)) %>%
  addMarkers(data=subset(peaks,peaks@data$ele>10000),
             icon = peakIcons,
             popup=~paste("Name: ",name,"<br>Elevation: ", ele)) %>%
    addLegend(title = "Peak Elevation", pal = eleColor,
            values = ~ele, opacity = 1, position="bottomleft") %>%
    addPolylines(data=yosemite, fillOpacity = 0, dashArray=c(10,10), fill=FALSE, color="blue")

• Color coding using colorBin()

• Color coding using eleColor <- colorBin(spectral, peaks@data$ele)

You can use the function addProviderTiles() to change the background map, sometimes called the 'basemap'. To view the options for background maps, visit http://leaflet-extras.github.io/leaflet-providers/preview/.

So we don't have to retype our code every time, lets save our map (without a basemap) as a variable:

peakMap <- leaflet() %>%
  addCircleMarkers(data=peaks, weight=0, radius=~ele/1000, fillOpacity=0.7, color = ~eleColor(ele),
                   popup=~paste("Name: ",name,"<br>Elevation: ",ele)) %>%
  addLegend(title = "Peak Elevation", pal = eleColor,
            values = peaks@data$ele, opacity = 1, position="bottomleft") %>%
  addMarkers(data=subset(peaks,peaks@data$ele>10000),
             icon = peakIcons,
             popup=~paste("Name: ",name,"<br>Elevation: ",ele))

Great, now we can call peakMap and just add in different types of basemaps using addProviderTiles

mapbox <- "http://api.tiles.mapbox.com/v4/mapbox.outdoors/{z}/{x}/{y}.png?access_token=pk.eyJ1Ijoiam9zaHBlcHBlciIsImEiOiJuTWdrY2k4In0.HCCXtgU04scrTB_-ON4kjA"
peakMap %>% addTiles(urlTemplate = mapbox)

You can even pull in weather data. In this exmaple, I've overlaid weather data on top of the CartoDB.Positron basemap.

leaflet() %>% addProviderTiles("CartoDB.Positron") %>%
  addProviderTiles("OpenWeatherMap.Temperature", options=providerTileOptions(opacity=0.2)) %>%
  setView(lng = -122.2579335, lat = 37.8700441, zoom=4)

To add 'controls' to our map, we use the function addLayersControl(). We assign a group to each basemap and layer (polygon, marker, line, etc). Then layer switcher allows us to toggle between different basemaps and turn on/off each of the layers.

leaflet() %>%
  addCircleMarkers(data=peaks, weight=0, radius=~ele/1000,
                   fillOpacity=0.7, color = ~eleColor(ele),
                   popup=~paste("Name: ",name,"<br>Elevation: ",ele),
                   group="Peaks") %>%
  addLegend(title = "Peak Elevation", pal = eleColor,
            values = peaks@data$ele, opacity = 1, position="bottomleft") %>%
  addMarkers(data=subset(peaks,peaks@data$ele>10000),
             icon = peakIcons, popup=~paste("Name: ",name,"<br>Elevation: ",ele),
             group="Mountain Icons") %>%
  addPolylines(data=yosemite, fillOpacity = 0, dashArray=c(10,10),
               fill=FALSE, color="#3288BD",
               group="Yosemite") %>%
  addPolylines(data=PCT, dashArray=c(10,10),
               fill=FALSE, color="#9E0142",
               group="PCT") %>%
  #continued on next slide...

#add basemaps
  addProviderTiles("CartoDB.Positron", group="Simple") %>%
  addProviderTiles("Esri.WorldImagery", group="Satellite") %>%
  addTiles(urlTemplate = mapbox, group="Outdoors") %>%
  addLayersControl(
    baseGroups = c("Simple", "Satellite", "Outdoors"),
    overlayGroups = c("Peaks","Mountain Icons","Yosemite","PCT"),
    options = layersControlOptions(collapsed = FALSE)
  )